<p>The incorporation of smart charging stations together with vehicle-to-building (V2B) frameworks signifies not only a technological evolution but also a pivotal step towards constructing smarter and environmentally friendly urban environments. This initiative actively contributes to the optimization of system resources while also enabling the incorporation of renewable energy resources. In this study, the authors propose the development of a intelligent management system for parking lots based on reinforcement learning (RL) algorithms, aiming to minimize building energy purchases from the grid while ensuring the efficient charging of electric vehicles (EVs). This approach seeks to optimize energy consumption by reducing reliance on external power sources and enhancing the charging process for EVs in a sustainable manner. Using that rule based controller as a benchmark, the RL algorithms obtained a 15 % to 17 % improvement in the evaluation reward. In the realm of grid energy, they saved 9 to 11% in average purchase cost. In essence, these algorithms, after training, make more efficient decisions than more traditional control methods while ensuring EV charging.</p>